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Friday, November 02, 2018

A special search approach lets you find people in surveillance video
just based on their description. The RT headline read, "AI algorithm can
find you in CCTV footage without using face recognition." But how?
Height, gender, clothing, not facial features, are the giveaways, via an
artificial intelligence algorithm, as Tech Xplore reports.

The work reflects the potential ofdeep learning techniques. RT makes a useful point for those who may still blur the concept of deep learning with machine learning. RT wrote that in the researchers' efforts, deep learning traveled "beyond machine learning (where patterns are set into algorithms and require supervision) by incorporating 'self-learning'- to train a convolutional neural network (CNN) to recognize soft biometrics using computer vision."RT and other sites reported on the team of researchers who created the tool that finds people in CCTV footage...

The authors in the abstract said that the color and gender models
were fine-tuned using AlexNet. The latter is a convolutional neural
network (CNN) that gets its name from its designer, Alex Krizhevsky. The
AlexNet is trained on more than 1 million images from the ImageNet
database, said MathWorks. "The network is 8 layers
deep and can classify images into 1000 object categories, such as
keyboard, mouse, pencil, and many animals. As a result, the network has
learned rich feature representations for a wide range of images."Read more...

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About Me

Hello, my name is Helge Scherlund and I am the Education Editor and Online Educator of this personal weblog and the founder of eLearning • Computer-Mediated Communication Center.
I have an education in the teaching adults and adult learning from Roskilde University, with Computer-Mediated Communication (CMC) and Human Resource Development (HRD) as specially studied subjects. I am the author of several articles and publications about the use of decision support tools, e-learning and computer-mediated communication. I am a member of The Danish Mathematical Society (DMF), The Danish Society for Theoretical Statistics (DSTS) and an individual member of the European Mathematical Society (EMS). Note: Comments published here are purely my own and do not reflect those of my current or future employers or other organizations.